Machine Learning Control Training#
Welcome to the documentation of the Transerflab’s Machine Learning Control training!
It contains the executed notebooks as pages introducing several concepts from Control Theory and more specifically Optimal Control Theory with examples as well as the much newer field of Machine Learning Control. It contains as well documentation of the source code.
Notebook Pages#
These pages contain all rendered notebooks and serve as a reference.
API Documentation#
These pages contain documentation of the training’s source code.
References#
Lukas Brunke, Melissa Greeff, Adam W. Hall, Zhaocong Yuan, Siqi Zhou, Jacopo Panerati, and Angela P. Schoellig. Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning. Annual Review of Control, Robotics, and Autonomous Systems, 5(1):411–444, May 2022. doi:10.1146/annurev-control-042920-020211.
Steven L. Brunton, Joshua L. Proctor, and J. Nathan Kutz. Discovering governing equations from data by sparse identification of nonlinear dynamical systems. Proceedings of the National Academy of Sciences, 113(15):3932–3937, April 2016. doi:10.1073/pnas.1517384113.
Steven L. Brunton, Joshua L. Proctor, and J. Nathan Kutz. Sparse Identification of Nonlinear Dynamics with Control (SINDYc). https://arxiv.org/abs/1605.06682v1, May 2016.
Matthew J. Colbrook. The Multiverse of Dynamic Mode Decomposition Algorithms. November 2023. doi:10.48550/arXiv.2312.00137.
Urban Fasel, Eurika Kaiser, J. Nathan Kutz, Bingni W. Brunton, and Steven L. Brunton. SINDy with Control: A Tutorial. https://arxiv.org/abs/2108.13404v1, August 2021.
Albert Gu, Karan Goel, and Christopher Re. Efficiently modeling long sequences with structured state spaces. In International Conference on Learning Representations. March 2022. arXiv:2111.00396.
Lukas Hewing, Kim P. Wabersich, Marcel Menner, and Melanie N. Zeilinger. Learning-Based Model Predictive Control: Toward Safe Learning in Control. Annual Review of Control, Robotics, and Autonomous Systems, 3(1):269–296, May 2020. doi:10.1146/annurev-control-090419-075625.
Joshua L. Proctor, Steven L. Brunton, and J. Nathan Kutz. Dynamic Mode Decomposition with Control. SIAM Journal on Applied Dynamical Systems, 15(1):142–161, January 2016. doi:10.1137/15M1013857.
Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, and Soon-Jo Chung. Neural Lander: Stable Drone Landing Control Using Learned Dynamics. In 2019 International Conference on Robotics and Automation (ICRA), 9784–9790. May 2019. doi:10.1109/ICRA.2019.8794351.